The invention relates to an apparatus and method for detecting flames. More particularly, the invention relates to an apparatus and method for detecting flames by measuring at least three regions of infrared radiation emitted by water vapor that is produced as a product of combustion.
Flames emit electromagnetic radiation across a range of wavelengths. The precise wavelengths may vary from flame to flame, depending on variables such as the fuel being burned. Conventional optical flame detectors operate by sensing one or more wavelengths of electromagnetic radiation.
Many combustible materials include carbon, and combustion of such fuels typically generates hot carbon dioxide. Hot carbon dioxide has a characteristic infrared emission spectrum, with a relatively strong and well-defined peak at wavelengths from approximately 4.2 to approximately 4.5 microns, and relatively little intensity at wavelengths immediately on either side of the peak.
An exemplary representation of an infrared emission spectrum including such a peak for carbon dioxide is shown in FIG. 1. The shape of the emission spectrum, including the precise wavelength of the maximum intensity, may vary somewhat depending on factors such as the type of fuel(s) burned, etc. However, regardless of its precise shape, this peak typically exhibits relatively strong emissions with relatively weak emissions immediately to either side.
For purposes of simplicity, this infrared carbon dioxide emissions peak is sometimes referred to herein as “the 4.4 micron peak”, although as noted the exact wavelengths included in the peak will not necessarily be limited only to 4.4 microns.
Such a peak enables convenient analysis of the infrared radiation in conventional devices. For example, a conventional flame detector might be sensitive to a band of infrared radiation aligned with the carbon dioxide emission peak. A high intensity signal in that band could be interpreted as an indication of the presence of hot carbon dioxide, and thus may be considered indicative of a flame.
The 4.4 micron carbon dioxide peak also facilitates simple comparisons of peak to non-peak signals in conventional devices. For example, a slightly different conventional flame detector might be sensitive to a band of infrared radiation centered on the peak itself, and also to a “side band” of infrared radiation near but not at the peak. In the presence of an actual fire, the radiation intensity in the peak band generally is high, while little or no radiation is received in the side band. Thus, high radiation intensity in the peak band as compared to that in the non-peak side band might be used to determine whether the peak, and perhaps a flame, is present.
However, not all flames generate significant quantities of carbon dioxide. Some fuels lack carbon altogether, and thus do not produce carbon dioxide when burned. Exemplary carbon-free fuels include, but are not limited to, molecular hydrogen (H2), ammonia (NH3), arsine (AsH3), and silane (SiH4). Since burning these fuels does not produce carbon dioxide, sensing the characteristic infrared emission spectrum of carbon dioxide will not be a reliable approach for detecting such flames.
Attempts have been made to produce a flame detector that is sensitive to flames burning carbon-free fuels.
For example, the infrared radiation emitted by flames is not limited only to the characteristic radiation of hot carbon dioxide. For example, many fuels comprising hydrogen (including some fuels that also comprise carbon) produce water vapor when burned. Like carbon dioxide, water vapor has a characteristic infrared emission spectrum. The water emission spectrum extends from approximately 2.3 microns to 3.5 microns. Flames may also emit radiation at many other infrared wavelengths. Some conventional detectors sense portions of the infrared spectrum other than the 4.4 micron carbon dioxide peak.
However, the infrared emission spectra produced by burning carbon-free fuels typically is different from the infrared emission spectra produced by burning carbon-bearing fuels. As noted, carbon bearing fuels typically produce carbon dioxide, and their emission spectra thus typically exhibit the 4.4 micron carbon dioxide peak. However, the emission spectra of carbon-free fuels, which due to their lack of carbon do not generate significant quantities of carbon dioxide, typically do not exhibit the 4.4 micron carbon dioxide peak. Moreover, the emission spectra of carbon-free fuels may not exhibit any other similarly well-defined peak that might be analyzed in a similar conventional manner.
As differentiated from the carbon dioxide peak, much of the infrared spectra for flames burning many fuels (both carbon-bearing and carbon-free) is in the form of broad emission bands, small individual peaks of relatively low intensity, or tightly spaced groups of peaks. For example, an infrared emission spectrum for water vapor is shown in FIG. 2. As may be seen therein, no strong peak or other clear marker is readily visible. A magnified view of a portion of the infrared water emission spectrum is shown in FIG. 3. Although peaks may be seen therein, those peaks are many in number, and tightly spaced. In addition, many of those peaks are of at least roughly comparable height. Given such an emission spectrum, conventional analysis of a single peak may prove difficult.
Although much of the infrared spectrum may vary depending on variables such as the type of fuel being burned, certain bands of the infrared spectrum may be emitted with some consistency from a variety of flames. For example, flames burning fuels that include hydrogen generally produce hot water vapor as a combustion product, and their infrared emission spectra typically include a water emission band. However, conventional analysis of those portions of the infrared flame spectrum has not provided a reliable indication of the presence of flames, and/or has not reliably excluded false alarm sources.
As noted above, flame detection conventionally relies on measurements of radiation in a band associated with a peak, with low intensity areas immediately to either side. However, with closely spaced peaks as shown in FIGS. 2 and 3, defining areas of low intensity to either side of a particular peak may be difficult. In order to select only one peak from a group of many closely spaced peaks in a spectrum similar to that shown in FIGS. 2 and 3, some means of limiting the radiation detected to a very narrow band would be required. As may be seen from FIG. 1, a bandwidth of 0.1 or 0.2 microns might be suitable to isolate the 4.4 micron carbon dioxide peak. However, as may be seen from FIG. 3, isolating one of the peaks therein might require a bandwidth as small as 0.001 microns. Even if achieving such a narrow bandwidth is possible, it may be impractical.
In addition, any such band would have to be aligned to the selected peak with a very high degree of precision. If the peak to be sensed is only 0.001 microns wide, a misalignment of 0.001 microns might be enough to miss the peak entirely. Again, assuming a design is available to provide such precision in aligning the band to sense a peak such as those in FIG. 3, it may not be practical to manufacture.
Furthermore, the use of conventional optics changes the apparent wavelength of incident radiation. If the radiation is at least approximately normal to the surfaces of the optics, the apparent change in wavelength may be small. However, for incident radiation striking at an off-axis angle of 45 degrees, the apparent wavelength of the incident radiation may decrease by as much as 2 or 3 percent. Considering the peak shown at approximately 2.82 microns in FIG. 3, a 2 percent variation would be approximately 0.06 microns. This variation is many times the 0.001 micron bandwidth discussed above.
Thus, even if a filter or other selector can be made with a suitably small bandwidth and a suitably precise pass band, a conventional approach to flame detection using a water emission band (or a band similarly lacking in readily isolated peaks) still would face significant obstacles to success in detecting actual flames.
In addition, infrared radiation with spectra at least superficially similar to those emitted by flames is produced by many non-flame sources, including but not limited to warm objects (including under some circumstances people or animals), sunlight, and various forms of artificial lighting. Infrared radiation from these sources may be misinterpreted as a flame, thus producing a false alarm condition. However, simply ignoring or filtering the radiation to exclude false alarms from such non-flame sources may result in actual flames being masked.
Absent a strong peak or other well-defined marker, attempts have been made conventionally to distinguish flames from false alarm sources by sensing wavelengths to identify the relative shape of an infrared signal overall, rather than keying off of a particular characteristic feature. For example, many false alarm sources have infrared spectra resembling a blackbody curve, but actual soot-free fires generally do not.
Conventionally, however, it may be difficult to determine reliably whether the overall shape of an infrared signal, particularly one that is broadly distributed in terms of wavelength, and/or of relatively low intensity, is representative of a fire or a false alarm source.
Conventionally, when attempting to identify differences in the shape of an overall spectrum, wavelengths are considered that show plainly visible changes intensity between flames and false alarm sources.
However, such an arrangement is not necessarily sufficient to distinguish between an actual fire and a false alarm. Many wavelengths that exhibit variations in strength between false alarms and fires also exhibit variations for different types of false alarms, and/or different types of fires.
In addition, the overall shape of the spectrum of infrared radiation emitted by false alarm sources also may vary. Thus, a ratio of two given wavelengths may vary considerably for differing false alarm sources.
For example, the amount of radiation emitted at different wavelengths may vary considerably, depending on the temperature or other properties of the false alarm source.
Even if all false alarm sources are assumed to be simple blackbody radiators (which may not necessarily be the case), the temperatures of those blackbodies may vary dramatically. The sun has an effective blackbody temperature of approximately 5800 Kelvin, while objects near room temperature have blackbody temperatures of approximately 300 Kelvin.
Thus, the ratio of signal strength at two given wavelengths may have a range of values, whether the source of the infrared radiation is a flame or a false alarm source. Consequently, such an arrangement may not be sufficient to reliably distinguish flames from false alarms.
If the shape of an infrared signal is mapped out in greater detail, for example by increasing the number of infrared wavelengths for which signal intensity is measured, this may at least in principle enable greater confidence in determining whether a signal is from a real fire or a false alarm source. However, increasing the number of monitored bands can increase the complexity of a detector. For example, as the number of wavelengths monitored increases, more sensors, filters, lens systems, etc. are needed. Also, as the number of individual wavelengths considered increases, the amount of processing power required also may increase.
In summary, using conventional approaches for infrared sensing of flames from carbon-free fuels may pose difficulties with regard to accurate detection of flames, reliability in rejecting false alarms, and complexity.
It is known to rely on wavelengths other than infrared when attempting to detect flames from carbon-free fuels. However, conventional approaches for sensing ultraviolet and/or visible radiation from flames burning carbon-free fuels may pose similar difficulties to those described with regard to the conventional sensing of infrared radiation.
Some carbon-free fuels, such as molecular hydrogen, emit ultraviolet radiation when burned. Some conventional flame detectors rely on this ultraviolet radiation in order to identify the presence of carbon-free fuel flames.
However, for many fuels the ultraviolet emission spectrum is weak and/or spread out. Instead of exhibiting a strong, well-defined emission peak, ultraviolet spectra for flames may consist of broad, low-intensity emission bands or many small, closely grouped peaks.
As noted above, the lack of a strong infrared peak poses difficulties for conventional infrared detectors. The lack of a well-defined ultraviolet peak presents similar difficulties for ultraviolet detectors.
In addition, as with conventional infrared detectors, false alarms are also a concern with ultraviolet flame detectors. Ultraviolet radiation with wavelengths similar to those emitted by flames is produced by many non-flame sources, including but not limited to electrical equipment, electrical discharges such as those associated with arc welding and lightning, and coronal discharges such as those from power lines.
In addition, certain gases absorb ultraviolet energy. In particular, certain hydrocarbons readily absorb ultraviolet radiation. The presence of hydrocarbon vapors may be expected in applications such as petroleum drilling, refining, and storage. Indeed, the presence of such vapors may serve as a stimulus to provide flame detection capability. However, those vapors may absorb ultraviolet radiation that is relied upon by some conventional flame detectors. Consequently, the vapors themselves may interfere with conventional flame detection, and/or false alarm exclusion.
Sensing visible light also has been considered for detecting carbon-free fuel flames. As is well-known, certain flames emit visible light. However, many carbon-free fuels emit only minimal amounts of visible radiation. In particular, molecular hydrogen is notoriously difficult to identify in visible light. The visible light spectra for such fires tend to have relatively weak signals, with few if any well defined peaks.
Also, as with infrared and ultraviolet radiation, visible light similar to light that may be emitted by flames also is emitted by many non-flame sources, such as sunlight, incandescent lamps, fluorescent lights, etc.
It has been known to combine infrared detection with ultraviolet detection and/or visible light detection. However, such combinations conventionally may suffer from limitations similar to those of their individual spectra. For example, a conventional UV-IR flame detector may be unable to detect ultraviolet light in the presence of hydrocarbons; if ultraviolet radiation is relied upon by that detector in order to identify a fire and/or exclude false alarm sources, the lack of that ultraviolet radiation at the detector due to the presence of hydrocarbons may interfere with the detector's operation.
Thus, conventional approaches for using visible light to reliably detect carbon-free flames while avoiding false alarms also may be problematical.
Even for burning fuels that include carbon, and that emit hot carbon dioxide, conventional reliance on the carbon dioxide peak at 4.4 microns may pose difficulties in at least some circumstances.
For example, contaminants that affect the transmission of radiation in the 4.4 micron emission band are of concern.
One such potential contaminant is cool carbon dioxide. Cool carbon dioxide readily absorbs the infrared radiation emitted by hot carbon dioxide. Thus, the presence of significant amounts of cool carbon dioxide may reduce the apparent intensity of radiation at 4.4 microns. This may reduce the sensitivity of conventional carbon dioxide spectrum flame detectors.
It is noted that cool carbon dioxide is widely used as a fire suppressant. As such, it may be deliberately present in high concentrations when a fire is or is believed to be present. However, the very act of suppressing that fire may effectively “blind” conventional carbon dioxide spectrum flame detectors in the vicinity. In such circumstances, it might be difficult to determine whether the fire is extinguished or is still burning without clearing the area of the carbon dioxide fire suppressant.
Moreover, conventional carbon dioxide spectrum infrared flame detectors may have at best limited facility for discriminating between distant fires and fires within the area they are tasked to protect. With conventional carbon dioxide spectrum infrared flame detectors it may be difficult to distinguish between a flame that is present in a monitored area, and thus represents a potential hazard, and a flame that is far from the monitored area.
For example, petroleum drilling and processing facilities often have large stack fires or “flares” that burn off hydrocarbon gas. Typically, such hydrocarbon fires emit infrared radiation characteristic of hot carbon dioxide, including the peak at 4.4 microns. Stack flares typically represent known phenomena, and generally are not considered a legitimate alarm source.
However, stack flares often are visible for miles. It may be difficult to distinguish with a conventional carbon dioxide spectrum infrared flame detector between a distant stack flare and a potentially hazardous flame nearby. Thus, if a stack flare is within the field of view of a conventional carbon dioxide spectrum infrared flame detector, the conventional detector may trigger an alarm condition based on the presence of a 4.4 micron signal from the stack flare, even if the stack flare (or other fire) is far outside the desired area to be protected.